[Adapt] Reminder: Talk by Chengkai Li @ 3 PM, Room 414

Kenny Zhu kzhu at cs.sjtu.edu.cn
Wed Dec 18 09:33:14 CST 2013

Title: Tackling Usability Challenges in Querying and Exploring Entity Graphs


Time: Wednesday, Dec 18, 2013, 3 PM

Venue: SEIEE-03-414

Host: Kenny Q. Zhu (朱其立)




We witness an unprecedented proliferation of entity graphs that capture
entities (e.g., persons, products, organizations) and their relationships.
Real-world entity graphs include knowledge bases, social graphs, citation
graphs, drug and disease databases, and program analysis graphs, to name
just a few. Users and developers are trying hard to tap into entity graphs
for numerous applications, including search, recommendation systems,
business intelligence and health informatics.  Both users and application
developers are often overwhelmed by the daunting task of understanding and
using entity graphs. The challenges lie in the gap between complex/big data
and non-expert users. In retrieving data from entity graphs, the norm is
often to use structured query languages such as SQL, SPARQL, and those
alike. However, graph data is not “easier” than relational data in either
query language or data model. If querying “simple” tables is difficult,
aren’t complex graphs harder to query?


In this talk, I will introduce my group's ongoing efforts in tackling the
usability challenges in querying and exploring entity graphs. Specifically,
I will discuss GQBE, a system that queries graphs by examples and TableView,
a technique that generates preview tables for entity graphs. I will also
give an overview of our projects on computational journalism and entity
query/exploration in Web text.





Dr. Chengkai Li is an Associate Professor in the Department of Computer
Science and Engineering at the University of Texas at Arlington. He received
his Ph.D. degree in Computer Science from the University of Illinois at
Urbana-Champaign in 2007, and an M.E. and a B.S. degree in Computer Science
from Nanjing University, in 2000 and 1997, respectively. After graduation in
2007, he became an Assistant Professor in the Computer Science and
Engineering Department of UT Arlington and was promoted to Associate
Professor in 2013. Dr. Li's research interests are in the areas of database,
data mining and information retrieval, with the current emphasis on building
large-scale human-assisting and human-assisted data and information systems
with high usability, low cost and applications for social good. In
particular, he works on computational journalism, crowdsourcing and human
computation, database exploration by ranking (top-k), skyline and preference
queries, database testing, entity search, query and exploration, query
processing and optimization, usability challenges in using entity graphs,
and Web data management. Dr. Li's papers have appeared in prestigious
database, data mining and Web conferences including SIGMOD, VLDB, ICDE,
EDBT, KDD, WWW, WSDM and CIKM, as well as in several leading journals such
as TKDD and TKDE. He has served in the organizing committee of IEEE IPCCC
several times (as General Co-Chair in 2012 and Program Co-Chair in 2010) and
in the program committees of premier conferences such as VLDB, ICDE, EDBT,
WWW, CIKM and ICDM. He has also been a reviewer for multiple prestigious
journals, e.g., TODS, TOIS, TKDE and VLDB Journal. Dr. Li is a recipient of
the 2011 and 2012 HP Labs Innovation Research Award.



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